Data analytics technologies and techniques are widely used in commercial industries to enable organizations to make more-informed business decisions and by scientists and researchers to verify or disprove scientific models, theories and hypotheses. Specialized computer systems and software can be used to examine data sets in order to draw conclusions about the information they contain. Data in the data sets may be extracted and categorized to identify and analyze data trends and patterns. The data analytics may, for example, involve use of statistical tools (e.g., clustering or partitioning) to group data having similar characteristics or properties in “clusters” as a possible explanation of trends or patterns in data.
The data analytics technologies and techniques provided by these computer systems and software may include provisions for visual analytics i.e. analytical reasoning facilitated by interactive visual interfaces. Visual analytics can be used to attack certain problems whose size, complexity, and need for closely coupled human and machine analysis may make them otherwise intractable.
Consideration is now being given to systems and techniques for human-computer interaction in the context of data analytics. In particular, attention is directed toward interactive visual interfaces for users to interact with data sets and visually explore the data.